Distributed virtual selective-forwarding units and SDN-assisted edge computing for optimization of multi-party WebRTC videoconferencing

Abstract

Network service providers (NSP) have growing interest in placing network intelligence and services at network edges by deploying software-defined network (SDN) and network function virtualization infrastructure. In multi-party WebRTC videoconferencing using scalable video coding, a selective forwarding unit (SFU) provides connectivity between peers with heterogeneous bandwidth and terminals. An important question is where in the network to place the SFU service in order to minimize end-to-end delay between all pairs of peers. Clearly, there is no single optimal place for a cloud SFU for all possible peer locations. We propose placing virtual SFUs at network edges leveraging NSP edge datacenters to optimize end-to-end delay and usage of overall network resources. The main advantage of the distributed edge-SFU framework is that each peer video stream travels the shortest path to reach other peers similar to mesh connection model, whereas each peer uploads a single stream to its edge-SFU avoiding the upload bottleneck. While the proposed distributed edge-SFU framework applies to both best-effort and managed service models, this paper proposes a premium managed, edge-integrated multi-party WebRTC service architecture with bandwidth and delay guarantees within access networks by SDN-assisted slicing of edge networks. The performance of the proposed distributed edge-SFU service architecture is demonstrated by means of experimental results.